基于双频谱脑电信号的脑-机交互理论、方法及其在建筑施工风险识别中的应用

项目名称： 基于双频谱脑电信号的脑-机交互理论、方法及其在建筑施工风险识别中的应用

项目编号： No.51508487

项目类型： 青年科学基金项目

立项/批准年度： 2016

项目学科： 建筑环境与结构工程学科

项目作者： 陈嘉宇

作者单位： 香港城市大学深圳研究院

项目金额： 20万元

中文摘要： 人员伤亡往往会对项目及工程公司造成巨大的生命与财产损失。近70%的伤亡事故都与施工人员的活动密切相关，因此监测并预防这些与人为活动相关的风险是提高施工安全的关键。研究表明施工人员的生理及心理状况对人的行为及安全具有重大的影响。近年在神经学的研究也指出由过度脑力负荷引起的无意视盲是引发事故的重要因素。同时，由于施工工程的复杂性及风险性会对施工人员脑力负荷有较高要求，容易导致脑力负荷过度并造成意外伤亡。然而，现有的施工技术与设备不具备监测工人脑力负荷的能力。本课题旨在开发能够监测脑力负荷的可穿戴脑电信号检测设备，并通过时频分析建立模型对施工人员的风险进行评估。

中文关键词： 施工管理；施工安全；脑电分析；脑力负荷；施工自动化

英文摘要： Construction companies can accrue losses due to labor fatalities and injuries. Since more than 70% of all accidents are related to human activities, detecting and mitigating human-related risks holds the key to improving the safety conditions within the construction industry. Previous research has revealed that the psychological and emotional conditions of workers can contribute to fatalities and injuries. Recent observations in the area of neural science and psychology suggest inattentional blindness is one major cause of unexpected human related accidents. Due to the limitation of human mental workload, laborers are vulnerable to unexpected hazards while focusing on complicated construction tasks. Therefore, the ability to detect the mental conditions of workers could reduce unexpected injuries. However, there are currently no available measurement approaches or devices capable of monitoring construction workers’ mental conditions. The research proposed in this paper aims to develop a measurement approach to evaluate hazards through neural time-frequency analysis. The research also describes the development of a prototype for a wearable Electroencephalography (EEG) safety helmet that enables the collection of the neural information required as input for the measurement approach.

英文关键词： Construction Management;Construction Safety;EEG analysis;Mental workload;Automation in Construction